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--- |
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base_model: UCLAML/mistral-7b-expert-iteration-iter3 |
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datasets: |
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- synthetic_data_mistral-7b-instruct-expert-iteration-iter3_score |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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- autoquant |
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- gptq |
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model-index: |
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- name: UCLAML/mistral-7b-expert-iteration-iter3 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Mistral-7B-Instruct-EI-Iter3 |
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This model is a GPTQ version of [UCLAML/mistral-7b-expert-iteration-iter3](UCLAML/mistral-7b-expert-iteration-iter3) |
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Created with [AutoQuant](https://colab.research.google.com/drive/1b6nqC7UZVt8bx4MksX7s656GXPM-eWw4?usp=sharing) |
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## Model description |
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I like the GPTQ format, this is 8bit, GROUP_SIZE 32. |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.6652 | 1.0 | 106 | 0.4722 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.19.1 |
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